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Aims: Loranthus tanakae Franch. & Sav is a medicinal plant that has a variety of pharmacological properties. However, its study is currently limited because of its relative shortage of natural abundance. The objective of this work was to find an alternative resource from this plant that could produce its bioactive ingredients. Methods and Results: We isolated endophytic fungi from the twigs of Loranthus tanakae Franch. & Sav and eight flavonoid-producing endophytic fungi were selected. The eight endophytic fungi meeting the criteria were identified as Alternaria tenuissima, Dothiorella gregaria, Penicillium aethiopicum, Nothophoma quercina and Hypoxylon perforatum by morphological and molecular methods. The antioxidant and antibacterial activities of the flavonoid-producing endophytic fungi were investigated in vitro, where Alternaria tenuissima ZP28 and ZM148 demonstrated greater activities than the other six strains. Flavonoids of ZP28 and ZM148 were preliminarily identified by liquid chromatography-mass spectrometry (LC-MS). Conclusion:After screening the flavonoid-producing endophytic fungi, Alternaria tenuissima ZP28 and ZM148 were found to have good antioxidant and antibacterial activities. Overall, this study provided new direction and resources for the acquisition of flavonoids.Significance and impact of the study: Endophytic fungi are a promising alternative approach for the large-scale production of flavonoids from Loranthus tanakae Franch. & Sav.

This study aims to explore the factors determining consumer loyalty to real estate agents. Based on the past literature regarding the factors of loyalty, the study considers physical attractiveness and intellectual competence combined with a traditional loyalty model in proposing its conceptual framework. It then estimates the relevant parameters using a linear structural equation model (SEM). The subjects of the study consist of consumers in Kaohsiung City, Taiwan, aged at least 20 years old who have experience in engaging the services of real estate companies during housing transactions. A total of 300 questionnaires were distributed, with 268 valid ones being returned, for a valid return rate of 89.33%. According to the empirical results, physical attractiveness indirectly influences satisfaction through trust and intellectual competence, with satisfaction in turn affecting customer loyalty. The effect of physical attractiveness on satisfaction through trust is more significant than its effect on satisfaction through intellectual competence. These findings show that the relationship among physical attractiveness, intellectual competence, and trust plays an important role in determining satisfaction and loyalty. Past studies related to loyalty introduced various factors of loyalty; however, they rarely explored the effects of physical attractiveness and intellectual competence on loyalty. That is the difference between this study and past research.

Plant secondary metabolites (SMs) play a crucial role in plant defense against pathogens and adaptation to environmental stresses, some of which are produced from medicinal plants and are the material basis of clinical efficacy and vital indicators for quality evaluation of corresponding medicinal materials. The influence of plant microbiota on plant nutrient uptake, production, and stress tolerance has been revealed, but the associations between plant microbiota and the accumulation of SMs in medicinal plants remain largely unknown. Plant SMs can vary among individuals, which could be partly ascribed to the shift in microbial community associated with the plant host. In the present study, we sampled fine roots and rhizosphere soils of Sophora flavescens grown in four well-separated cities/counties in China and determined the taxonomic composition of rhizosphere bacterial communities using Illumina 16S amplicon sequencing. In addition, the association of the rhizosphere bacterial microbiota with the accumulation of alkaloids in the roots of S. flavescens was analyzed. The results showed that S. flavescens hosted distinct bacterial communities in the rhizosphere across geographic locations and plant ages, also indicating that geographic location was a larger source of variation than plant age. Moreover, redundancy analysis revealed that spatial, climatic (mean annual temperature and precipitation), and edaphic factors (pH and available N and P) were the key drivers that shape the rhizosphere bacterial communities. Furthermore, the results of the Mantel test demonstrated that the rhizosphere bacterial microbiota was remarkably correlated with the contents of oxymatrine, sophoridine, and matrine + oxymatrine in roots. Specific taxa belonging to Actinobacteria and Chloroflexi were identified as potential beneficial bacteria associated with the total accumulation of matrine and oxymatrine by a random forest machine learning algorithm. Finally, the structural equation modeling indicated that the Actinobacteria phylum had a direct effect on the total accumulation of matrine and oxymatrine. The present study addresses the association between the rhizosphere bacterial communities and the accumulation of alkaloids in the medicinal plant S. flavescens. Our findings may provide a basis for the quality improvement and sustainable utilization of this medicinal plant thorough rhizosphere microbiota manipulation.

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Existing research suggests that COVID-19 lockdowns tend to contribute to a decrease in overall urban crime rates. Most studies have compared pre-lockdown and post-lockdown periods to lockdown periods in Western cities. Few have touched on the fine variations during lockdowns. Equally rare are intracity studies conducted in China. This study tested the relationship between violent crime and COVID-19 lockdown policies in ZG City in southern China. The distance from the isolation location to the nearest violent crime site, called “the nearest crime distance”, is a key variable in this study. Kernel density mapping and the Wilcoxon signed-rank test are used to compare the pre-lockdown and post-lockdown periods to the lockdown period. Panel logistic regression is used to test the fine variations among different stages during the lockdown. The result found an overall decline in violent crime during the lockdown and a bounce-back post-lockdown. Violent crime moved away from the isolation location during the lockdown. This outward spread continued for the first two months after the lifting of the lockdown, suggesting a lasting effect of the lockdown policy. During the lockdown, weekly changes in COVID-19 risk ratings at the district level in ZG City also affected changes in the nearest crime distance. In particular, an increase in the risk rating increased that distance, and a drop in the risk rating decreased that distance. These findings add new results to the literature and could have policy implications for joint crime and pandemic prevention and control.

Purpose Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been a great impact on human survival and a great threat to public health in countries all over the world. The link between COVID-19 and ocular illness has received increasing attention due to SARS-CoV-2 infection can be transmitted through eye contact. Using bioinformatics methods, we sought to investigate the potential molecular mechanisms between uveitis and COVID-19, providing rationales and directions for further exploration. Methods Transcriptomic data of uveitis and COVID-19 patient blood samples were accessed from the Gene Expression Omnibus public database. Common differentially expressed genes were identified. Genetic Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, Protein-Protein Interaction network analysis were performed on intersected genes. We screened 5 hub genes by using the maximum clustering centrality algorithm. The Least Absolute Shrinkage and Selection Operator regression analysis identified the potential biomarkers for uveitis and COVID-19. Finally, the expression level and diagnostic value of the biomarker in the two diseases were determined. Results 50 intersected genes were extracted from differential expression analysis in uveitis and COVID-19. These genes were functionally enriched in cytokine-mediated signaling pathway, vesicle lumen, receptor ligand activity. Through KEGG analysis, these genes were found to be involved in viral protein interaction with cytokine and cytokine receptor, and cytokine-cytokine receptor interaction. HORMAD1 was obtained by Least Absolute Shrinkage and Selection Operator regression analysis, which was high expression in both uveitis and COVID-19 when compared to controls. Receiver Operating Characteristic values and AUC statistics indicated that HORMAD1 had diagnostic value for uveitis and COVID-19. Conclusions Bioinformatic analysis predicts HORMAD1 involvement in etiology and therapeutic targets of uveitis and COVID-19. However, additional clinical trials and studies are needed to confirm the role of HORMAD1.